INTRODUCTION TO PROBABILITY AND STATISTICS is one of the first texts published by Duxbury and has been blending innovation with tradition for over thirty years. It was the first statistics text to include case studies in it, and now in the eleventh edition, this text is the first to include java applets in the body of the text. It has been used by hundreds of thousands of students since its first edition. This new edition retains the excellent examples, exercises and exposition that have made it a market leader, and builds upon this tradition of excellence with new technology integration.

Benefits:

NEW! "Do It Yourself" activities in the text incorporate over 30 interactive Java applets featured on the accompanying CD-ROM. These applets allow students to see statistical methods come to life as they test theories and reinforce concepts. 5-8 exercises accompany each of these interactive applets, allowing you to easily integrate them in to the classroom.

NEW! There are hundreds of new and updated exercises and examples. Additionally, classic exercises and examples will be posted on our website.

"How Do I" boxes provide step-by-step hints for solving problems.

"About Minitab" sections at the end of each chapter include instructions for generating Minitab output with discussions that refer to visual screen captures from Minitab 14.

"Key Concepts and Formulas" sections at the end of each chapter provide quick reference for students before tests and assignments.

A free CD-ROM is packaged with every copy of the text. The CD includes over 30 interactive Java applets, PowerPoint slides, a tutorial program that offers practice exercises with immediate feedback, and data sets for the exercises in the text.

Many examples and exercises use real data sets. This helps students see the connections between their studies and their lives.

Over 35 years of teaching and writing experience contribute to the clear exposition and interesting, effective examples and exercises.

2. DESCRIBING DATA WITH NUMERICAL MEASURES. Describing a Set of Data with Numerical Measures. Measures of Center. Measures of Variability. On the Practical Significance of the Standard Deviation. A Check on the Calculation of s. Measures of Relative Standing. The Five-number Summary and the Box Plot. Key Concepts and Formulas. About MINITAB-Numerical Descriptive Measures. Case Study: The Boys of Summer.

6. THE NORMAL PROBABILITY DISTRIBUTION. Probability Distributions for Continuous Random Variables. The Normal Probability Distribution. Tabulated Areas of the Normal Probability Distribution. The Normal Approximation to the Binomial Probability Distribution (Optional). Key Concepts and Formulas. About MINITAB--Normal Probabilities. Case Study: The Long and Short of It.

8. LARGE-SAMPLE ESTIMATION. Where We've Been. Where We're Going-Statistical Inference. Types of Estimators. Point Estimation. Interval Estimation. Estimating the Difference between Two Population Means. Estimating the Difference between Two Binomial Proportions. One-Sided Confidence Bounds. Choosing the Sample Size. Key Concepts and Formulas. Case Study: How Reliable Is That Poll?

9. LARGE-SAMPLE TESTS OF HYPOTHESES. Testing Hypotheses about Population Parameters. A Statistical Test of Hypothesis. A Large-Sample Test about a Population Mean. A Large-Sample Test of Hypothesis for the Difference in Two Population Means. A Large-Sample Test of Hypothesis for a Binomial Proportion. A Large-Sample Test of Hypothesis for the Difference in Two Binomial Proportions. Some Comments on Testing Hypotheses. Key Concepts and Formulas. Case Study: An Aspirin a Day?

10. INFERENCE FROM SMALL SAMPLES. Introduction. Student's Distribution. Small-Sample Inferences Concerning a Population Mean. Small-Sample Inferences for the Difference between Two Population Means: Independent Random Samples. Small-Sample Inferences for the Difference between Two Means: A Paired Difference Test. Inferences Concerning a Population Variance. Comparing Two Population Variances. Revisiting the Small Sample Assumptions. Key Concepts and Formlas. About MINITAB--Small-Sample Testing and Estimation. Case Study: How Would You Like a Four-Day Work Week?

11. THE ANALYSIS OF VARIANCE. The Design of an Experiment. What Is an Analysis of Variance? The Assumptions for an Analysis of Variance. The Completely Randomized Design: A One-Way Classification. The Analysis of Variance for a Completely Randomized Design. Ranking Population Means. The Randomized Block Design: A Two-Way Classification. The Analysis of Variance for a Randomized Block Design. The a x b Factorial Experiment: A Two-Way Classification. The Analysis of Variance for an a x b Factorial Experiment. Revisiting the Analysis of Variance Assumptions. A Brief Summary. Key Concepts and Formulas. About MINITAB--Analysis of Variance Procedures. Case Study: "A Fine Mess".

12. LINEAR REGRESSION AND CORRELATION. Introduction. A Simple Linear Probabilistic Model. The Method of Least Squares. An Analysis of Variance for Linear Regression. Testing the Usefulness of the Linear Regression Model. Inferences Concerning B, the Slope of the Line of Means. The Analysis of Variance F Test. Measuring the Strength of the Relationship: The Coefficient of Determination. Interpreting the Results of a Significant Regression. Diagnostic Tools for Checking the Regression Assumptions. Dependent Error Terms. Residual Plots. Estimation and Prediction using the Fitted Line. Correlation Analysis. Key Concepts and Formulas. About MINITAB-Linear Regression Procedures. Case Study: Is Your Car "Made in the U.S.A."?

INTRODUCTION TO PROBABILITY AND STATISTICS is one of the first texts published by Duxbury and has been blending innovation with tradition for over thirty years. It was the first statistics text to include case studies in it, and now in the eleventh edition, this text is the first to include java applets in the body of the text. It has been used by hundreds of thousands of students since its first edition. This new edition retains the excellent examples, exercises and exposition that have made it a market leader, and builds upon this tradition of excellence with new technology integration.

Benefits:

NEW! "Do It Yourself" activities in the text incorporate over 30 interactive Java applets featured on the accompanying CD-ROM. These applets allow students to see statistical methods come to life as they test theories and reinforce concepts. 5-8 exercises accompany each of these interactive applets, allowing you to easily integrate them in to the classroom.

NEW! There are hundreds of new and updated exercises and examples. Additionally, classic exercises and examples will be posted on our website.

"How Do I" boxes provide step-by-step hints for solving problems.

"About Minitab" sections at the end of each chapter include instructions for generating Minitab output with discussions that refer to visual screen captures from Minitab 14.

"Key Concepts and Formulas" sections at the end of each chapter provide quick reference for students before tests and assignments.

A free CD-ROM is packaged with every copy of the text. The CD includes over 30 interactive Java applets, PowerPoint slides, a tutorial program that offers practice exercises with immediate feedback, and data sets for the exercises in the text.

Many examples and exercises use real data sets. This helps students see the connections between their studies and their lives.

Over 35 years of teaching and writing experience contribute to the clear exposition and interesting, effective examples and exercises.

2. DESCRIBING DATA WITH NUMERICAL MEASURES. Describing a Set of Data with Numerical Measures. Measures of Center. Measures of Variability. On the Practical Significance of the Standard Deviation. A Check on the Calculation of s. Measures of Relative Standing. The Five-number Summary and the Box Plot. Key Concepts and Formulas. About MINITAB-Numerical Descriptive Measures. Case Study: The Boys of Summer.

6. THE NORMAL PROBABILITY DISTRIBUTION. Probability Distributions for Continuous Random Variables. The Normal Probability Distribution. Tabulated Areas of the Normal Probability Distribution. The Normal Approximation to the Binomial Probability Distribution (Optional). Key Concepts and Formulas. About MINITAB--Normal Probabilities. Case Study: The Long and Short of It.

8. LARGE-SAMPLE ESTIMATION. Where We've Been. Where We're Going-Statistical Inference. Types of Estimators. Point Estimation. Interval Estimation. Estimating the Difference between Two Population Means. Estimating the Difference between Two Binomial Proportions. One-Sided Confidence Bounds. Choosing the Sample Size. Key Concepts and Formulas. Case Study: How Reliable Is That Poll?

9. LARGE-SAMPLE TESTS OF HYPOTHESES. Testing Hypotheses about Population Parameters. A Statistical Test of Hypothesis. A Large-Sample Test about a Population Mean. A Large-Sample Test of Hypothesis for the Difference in Two Population Means. A Large-Sample Test of Hypothesis for a Binomial Proportion. A Large-Sample Test of Hypothesis for the Difference in Two Binomial Proportions. Some Comments on Testing Hypotheses. Key Concepts and Formulas. Case Study: An Aspirin a Day?

10. INFERENCE FROM SMALL SAMPLES. Introduction. Student's Distribution. Small-Sample Inferences Concerning a Population Mean. Small-Sample Inferences for the Difference between Two Population Means: Independent Random Samples. Small-Sample Inferences for the Difference between Two Means: A Paired Difference Test. Inferences Concerning a Population Variance. Comparing Two Population Variances. Revisiting the Small Sample Assumptions. Key Concepts and Formlas. About MINITAB--Small-Sample Testing and Estimation. Case Study: How Would You Like a Four-Day Work Week?

11. THE ANALYSIS OF VARIANCE. The Design of an Experiment. What Is an Analysis of Variance? The Assumptions for an Analysis of Variance. The Completely Randomized Design: A One-Way Classification. The Analysis of Variance for a Completely Randomized Design. Ranking Population Means. The Randomized Block Design: A Two-Way Classification. The Analysis of Variance for a Randomized Block Design. The a x b Factorial Experiment: A Two-Way Classification. The Analysis of Variance for an a x b Factorial Experiment. Revisiting the Analysis of Variance Assumptions. A Brief Summary. Key Concepts and Formulas. About MINITAB--Analysis of Variance Procedures. Case Study: "A Fine Mess".

12. LINEAR REGRESSION AND CORRELATION. Introduction. A Simple Linear Probabilistic Model. The Method of Least Squares. An Analysis of Variance for Linear Regression. Testing the Usefulness of the Linear Regression Model. Inferences Concerning B, the Slope of the Line of Means. The Analysis of Variance F Test. Measuring the Strength of the Relationship: The Coefficient of Determination. Interpreting the Results of a Significant Regression. Diagnostic Tools for Checking the Regression Assumptions. Dependent Error Terms. Residual Plots. Estimation and Prediction using the Fitted Line. Correlation Analysis. Key Concepts and Formulas. About MINITAB-Linear Regression Procedures. Case Study: Is Your Car "Made in the U.S.A."?